Pharma's SpaceX Arrives: AI Drug Delivery Pioneer METiS Therapeutics Completes HKEX Listing, Completing the 'Big Three' of AI Pharma

With the advent of the AI era, all industries seem to have hit the fast-forward button. This is true for the pharmaceutical sector, and even more so for AI-driven pharmaceutical companies themselves.

XtalPi, which has just passed the hearing and knocked on the door of the Hong Kong Stock Exchange, is yet another vivid example of this era's transformation.

In just six years, XtalPi has completed the critical leap from a startup lab to an IPO company.. The key is, this is not a castle in the air ripened by capital, but rooted in the implementation of technology.

In terms of pipeline products, XtalPi has more than 10 pipelines, with the most advanced MTS-004 having successfully completed Phase III clinical trials. Meanwhile, based on its platform-based ecosystem, it has formed a "technology circle of friends" with over 30 pharmaceutical companies and institutions worldwide.

This "self-developed pipeline + platform services" dual-driven approach also makes its commercialization path clearly visible. It appears that,XtalPi Will Become a New Narrative in Observing AI Reshaping the Pharmaceutical Industry.

/ 01 / The world's first AI drug delivery stock, becoming the SpaceX of the pharmaceutical industry

The "new" aspect of XtalPi lies in its different underlying logic.

The essence of AI-driven drug discovery is to shift the process from "trial-and-error driven" to "rational design," significantly shortening the R&D cycle, reducing costs, and increasing success rates. This aligns with the original mission of JiTai Technology, and it is also the fundamental reason why it, along with Insilico Medicine and XtalPi, is widely recognized as one of the "three dragons" of AI-driven drug discovery in China.

But in fact, from the underlying logic, XtalPi belongs to a "new species."Its target is the reconstruction of the drug delivery logic.

From the perspective of the evolution history of global innovative drugs, this choice is not difficult to understand.

Currently, innovative drugs have evolved from small molecules to an era of flourishing diversity with biologics, mRNA, siRNA, gene editing, and cell therapy, placing increasingly high demands on delivery technologies. In the field of biologics, the delivery system directly determines the stability and drugability of the medication; for therapies such as mRNA, siRNA, and gene editing, delivery technology is the core bottleneck that decides whether the drug can be successfully developed, precisely targeted, and effectively delivered.

As Dr. Cai-Da Lai, co-founder and CEO of XtalPi, has judged,The real bottleneck for future innovative drugs is not in molecular design, but in delivery.He used the metaphor of "rockets and satellites" to explain the core logic ——"The drug is the satellite, and delivery is the rocket. If the rocket fails, even the best drug cannot become a medicine."。

Conversely, once delivery technology achieves a breakthrough and aids in drug development, its value will also be tremendous. Alnylam, with a market value exceeding 40 billion US dollars, is itself a story of "changing destiny" through the use of a delivery system. The company upgraded RNA interference (siRNA) therapy from relying on cumbersome, toxic delivery systems to the now "elegant" GalNAc conjugate delivery system that defines modern RNA drugs. It also revealed the unique mechanism behind achieving ultra-long-acting treatments, ultimately leading to sustained commercial success.

Of course, the current drug delivery technologies of various drugs still face many challenges, such as insufficient delivery precision and limited application scenarios. Therefore,Breaking through delivery bottlenecks has become a key direction for the industry's breakthrough, and this is also where XtalPi focuses its efforts.

Starting from the goal, XtalPi has successfully built the world's first artificial intelligence-driven nanodelivery platform, NanoForge.

NanoForge has four major components, namely "Basic Dry-Wet Experimental Data Layer Integrated Dry-Wet Laboratory Infrastructure, Database Layer METiS Ionizable Lipid Library, Model Layer METiS Artificial Intelligence Basic Model, Application Layer METiS Intelligent Agent". Specifically:

The basic dry-wet experimental data layer, as the "data production foundation," connects the dry and wet experimental processes, enabling real-time data synchronization and traceability, providing high-quality raw data for the closed loop.

Database Layer: METiS Ionizable Lipid Library is the "Data Reserve Core," serving as the world's largest LNP lipid library, continuously aggregating experimental data to provide core data support for model training and intelligent R&D.

Model Layer: METiS AI Foundation Model as the "Core Decision Brain," relies on multiple algorithms to accurately predict molecular performance and continuously iterates optimization through experimental results.

The METiS agent at the application layer is the execution terminal, which conducts targeted experimental validation based on predictions and transmits the results back to the database and model in real time.

The core value of this closed-loop is that it completely breaks the traditional "trial-and-error driven" model of nano-delivery research and development, achieving a paradigm of "rational design + closed-loop iteration":

On the one hand, through precise model predictions, the number of ineffective experiments has been significantly reduced, expanding the discovery scope of lipid molecules and nano-formulations, and breaking the limitations of traditional research and development;

On the other hand, through real-time data feedback and continuous model learning, the accuracy of research and development is constantly improved, reducing the preclinical delivery system R&D cycle from 1-2 years to less than 3 months, and it will be even faster in the future.

Based on NanoForge, XtalPi has successfully launched three core solutions:AiLNP (AI Nucleic Acid Delivery System Design Platform), AiRNA (AI mRNA Sequence Design Platform), and AiTEM (AI Small Molecule Formulation Design Platform) can not only provide new precise delivery pathways for small molecule drugs but also empower fields related to the "Third Drug Revolution," such as nucleic acid drugs and gene therapy, with potential on a global scale.BiopharmaceuticalsOccupying a key infrastructure position in industrial iteration.

In practice, the company has made considerable progress. Currently,XtalPi can achieve precise targeted delivery to eight major organs or tissues, forming a core barrier of "doing better what others can do, and breaking through what others have not yet reached."

At a more optimized level, its liver-targeting LNP delivery efficiency exceeds the industry benchmark by 20 times, with significant advantages in in vivo delivery.

In terms of breaking boundaries, XtalPi has overcome the challenge of extrahepatic delivery, achieving deep delivery to the lungs, muscles, heart, and tumor tissues, while precisely targeting the immune system such as the spleen and lymph nodes, paving the way for more new therapies.

If viewed from the perspective of the company's development ambition, the current achievements are merely the prelude. In the future, it will continue to iterate, optimize, and expand the two core platforms, AiLNP and AiRNA, making every effort to break through the existing boundaries of targeted delivery of nanomaterials.

Although the final outcome remains uncertain, the strategic positioning in key areas, combined with a technology-focused approach and a global vision of innovation ambition and breakthrough spirit, has earned XtalPi the reputation of being the "SpaceX of the pharmaceutical industry."

/ 02 / Rapid Proof, Ideals Become Reality

After several years of hype and bubble洗礼, the market has clearly realized that AI pharmaceuticals have never lacked grand narratives; what is most scarce are results that can be implemented, verified, and commercialized.Another core reason why XtalPi has become a unique case is that it has completed the technological closed-loop in an extremely short period of time, dispelling doubts about "remaining stuck in the lab."

First, the company has more than 10 pipeline products despite being established for only six years, including several discovery-stage candidates, four preclinical candidates, three clinical-stage products, one pre-NDA product, and two animal health products.Not only are they abundant in quantity, but they also span multiple fields, multi-target organs, and various drug forms.. More patents have been laid out at the patent level. As of April 17, 2026, the company has filed a total of 217 patent applications and has been granted 52 patents.

The above achievements verify the maturity and feasibility of its underlying technology platform, further demonstrating the platform's efficient empowerment capabilities for new drug modalities, while also indicating future potential. After all, whether in CNS, metabolism, oncology, or autoimmune diseases, they are all fields with the highest value in innovative drugs.

Secondly, the core technology has been clinically and academically validated, fully realizing the platform's value.

The company's fastest progressing core pipeline, MTS004, has successfully reached the primary endpoint of its Phase III clinical trial. It is the first AI-empowered innovative formulation drug in China to complete a Phase III clinical trial, directly validating the feasibility and industrial transformation capability of the technology platform at the clinical level.

From project initiation to the completion of Phase III clinical trials, it took only 38 months, significantly shorter than the approximately ten-year development cycle for traditional drugs, clearly demonstrating the remarkable advantages of AI-driven drug discovery in terms of efficiency and success rates. Meanwhile, MTS004 targets PBA (Pseudobulbar Affect), for which there are currently no approved treatments in China, giving it a clear first-mover advantage and the potential to fill the gap in PBA drug therapy within the country.

In addition to the clinical benchmark MTS-004, the company's academic achievements are equally outstanding.MTS105, as a liver-targeted delivery TCE solid tumor therapy, has demonstrated disruptive potential in high-efficiency expression, safety, potent tumor suppression, and long-term immune memory effects in vivo.，The relevant achievements have been published in "Nature Communications" and are expected to become the first-of-its-kind mRNA therapeutic drug, which can be used to treat liver cancer and other advanced solid tumors with liver metastasis.MTS-105 is currently in the IIT phase and has been granted Orphan Drug Designation by the US FDA.

At AACR 2026, XtalPi also launched MTS108 and MTS109, two mRNA-encoded trispecific TCE drugs, further leading the in vivo TCE research and development track.

Thirdly, despite being newly established, it boasts extensive and high-quality industry collaboration resources.

According to the prospectus, the company's current "circle of partners" showsLarge quantities, wide dimensions, high amountsThe three distinct characteristics.

First, with over 30 partners, such a scale of collaboration is quite rare for an innovative pharmaceutical company that has only been established for six years, fully demonstrating the industry's early recognition of its technical potential.

Secondly, the cooperation dimensions are diverse and comprehensive, having established deep binding relationships with multiple well-known pharmaceutical companies and top research institutions both in China and abroad. The scope of cooperation covers the entire chain, including joint technology development, pipeline collaboration, and the implementation of achievement transformation, realizing complementary advantages and resource synergy.

Finally, the total amount of cooperation has reached hundreds of millions of dollars. According to the prospectus, MTS-004 was out-licensed in September 2025, and the upfront payment of 100 million RMB has been received. The total milestone payments for MTS-004 in the PBA indication amount to 1.845 billion RMB, with additional potential milestone payments of up to 100 million RMB for potential indication expansion. Meanwhile, in the signed platform collaborations, the contract amount for a single target is as high as 109 million USD.

These multi-dimensional, high-value cooperative resources essentially represent the industry's comprehensive affirmation of the company's underlying technical strength, pipeline R&D capabilities, and commercialization potential. They also indicate that the company's dual-driven business model has been preliminarily market-validated.

The financial data reflects this point. In 2025, the company's revenue will be 11.29 times that of 2023. While maintaining R&D intensity (RMB 290 million, RMB 274 million, and RMB 270 million for 2023-2025 respectively), the loss has significantly narrowed from RMB 347 million in 2023 to RMB 180 million in 2025, which, to some extent, confirms the effectiveness of the business model.

/ 03 / "Flywheel" Acceleration, Efficiency Builds Moat

What makes XtalPi more anticipated in the market is its clear flywheel acceleration logic.

The long-term competitiveness of AI pharmaceuticals ultimately depends on itsThe Speed and Quality of the "Data-Algorithm-Experiment" Closed-loop Iteration, but this is also a recognized challenge in the industry. A major challenge AI faces in scientific research is how to obtain sufficient high-quality data to train effective models.

Even the popular AlphaFold is limited by insufficient complex structure data in drug discovery scenarios, impacting its practical application effectiveness. According to a March 2025 report in *Nature* magazine, AlphaFold faces a shortage of drug-related data, which directly affects model performance. Some scientists have noted that the foundational data AlphaFold relies on lacks samples of relevant interactions, hindering the tool's progress in applicable scenarios.

XtalPi seems to have solved the pain points of precision and data silos through a closed-loop approach.

As mentioned above, METiS' ionizable lipid library is the data universe of XtalPi. The reason it is named the "data universe" lies in its complete liberation from reliance on publicly available lipid structures —Not only does it have the world's largest and most diverse library of ionizable lipids, but it also possesses the highest-throughput experimental delivery model, along with an independent iteration cycle measured in months.

Relying on the solid foundation of the company's R&D closed loop, this "data universe" can continuously generate, test, and iterate new data, forming a self-reinforcing and ever-expanding data ecosystem without relying on external public data. This provides an inexhaustible core driving force for the company’s subsequent technology R&D and pipeline advancement.

Lai Caida once explained the AI delivery logic of XtalPi as follows: training AI models with massive data to plan the optimal delivery route for different drug molecules; every pipeline advancement and successful delivery will, in turn, enhance the model, making the system more precise and efficient.This self-reinforcing "flywheel" is precisely the deepest moat that XtalPi is trying to build.

At the same time, the rich resources and real-world output brought by the collaboration have also provided solid financial, technical, and channel support for the company’s subsequent technological iteration and upgrading, pipeline layout expansion, and commercialization progress. This is expected to further consolidate the cycle of technical reputation and core competitive advantages, laying a solid foundation for long-term development.

In fact,The company's operating system also follows this efficiency rule.. High efficiency has always been a distinct label for XtalPi, such as its solutions for drug delivery and formulation. Research and development began in 2020, pilot commercialization started in 2021, and full commercial implementation was achieved in 2024. The iteration speed far exceeds the industry average.

Under this logic,As XtalPi successfully goes public and gains support from the capital market, its development pace is expected to further accelerate.After all, the capital brings not only sufficient funds to support enterprises in achieving more comprehensive business expansion, but also provides diversified support for company development in multiple dimensions such as shareholder resources, industrial synergy, and brand endorsement. And these will become the fuel for the company's "flywheel" to accelerate.

Next, in an era of rational回归, whether 剂泰科技 can rely on its cutting-edge delivery technology to become a core player in the global biopharmaceutical industry revolution is worth continuous observation by the industry.

/ 04 / Summary

No matter what the future holds, XtalPi has already achieved remarkable success, proving to the industry through practice,How can scientists run an excellent innovative enterprise?

In the AI pharmaceuticals track, characterized by rotating hotspots and noisy concepts, XtalPi's success goes far beyond forward-looking strategic planning, manifesting in two key aspects:

First, adhere to restrained innovation.Not blindly chasing trends, but focusing on solving the industry-wide pain point of delivery, addressing real issues and delivering tangible results, paving a more pragmatic and convincing development path for AI-driven drug discovery.

Second, practice the long-termism of scientist entrepreneurship.Lai Caida leads his team to consistently focus on the hard technology of delivery, concentrating resources on the core aspects that determine the success or failure of drugs. They adhere to the R&D closed loop of “AI algorithms + high-throughput experiments + clinical validation,” deepening technical barriers, thoroughly conducting clinical validations, and realizing industrial value, thereby assisting in the innovation of drug development paradigms.

The above path not only demonstrates the precise judgment of scientists but also highlights the strategic determination of entrepreneurs:"With the rigor of scientists in R&D and the efficiency of entrepreneurs in implementation, we transform technological ideals into clinical realities at an accelerated pace."This also provides a high-quality reference model for more scientists to start their own businesses.

       Title: The Space X of the Pharmaceutical Industry Debuts, AI Drug Development Gathers the "Three Young Dragons"